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Books on the topic 'ROC (receiver operating characteristic) curve'

Author: Grafiati

Published: 3 June 2025

Last updated: 31 July 2025

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1

J, Hand D., ed. ROC curves for continuous data. Chapman & Hall/CRC, 2009.

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2

Matheja, Roswitha. Vergleichende Bildgütenuntersuchungen zweier Film-Folien-Systeme mit Weichstrahlraster sowie eines Film-Folien-Systems ohne Raster zum Einsatz für die Mammographie mittels receiver-operating-characteristic (ROC)-Analyse. [s.n.], 1985.

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3

He, Yaohua. Nonparametric methods for receiver operating characteristic (ROC) curve analysis in genomic studies and diagnostic medicine. 2006.

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4

Zou, Kelly H., Aiyi Liu, Andriy I. Bandos, Lucila Ohno-Machado, and Howard E. Rockette. Statistical Evaluation of Diagnostic Performance: Topics in ROC Analysis. Taylor & Francis Group, 2016.

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5

Zou, Kelly H. Statistical Evaluation of Diagnostic Performance: Topics in Roc Analysis. Taylor & Francis Group, 2011.

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6

Zou, Kelly H., Aiyi Liu, Andriy I. Bandos, Lucila Ohno-Machado, and Howard E. Rockette. Statistical Evaluation of Diagnostic Performance: Topics in ROC Analysis. Taylor & Francis Group, 2016.

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7

Statistical evaluation of diagnostic performance: Topics in ROC analysis. Taylor & Francis, 2012.

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8

Peacock, Janet L., Sally M. Kerry, and Raymond R. Balise. Single group studies. Oxford University Press, 2017. http://dx.doi.org/10.1093/med/9780198779100.003.0006.

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Chapter 6 discusses single group studies, and covers prevalence, how to present results, screening studies, calculating, and presenting sensitivity and specificity. It discusses how to deal with calculations with a rare condition where the numbers are small. Finally, it discusses the use of receiver operating characteristic (ROC) curves. The chapter includes analyses using Stata, SAS, SPSS, and R.

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9

Signal detection theory and ROC analysis in psychology and diagnostics: Collected papers. L. Erlbaum Associates, 1996.

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10

Observer Performance Methods for Diagnostic Imaging: Foundations, Modeling, and Applications with R-Based Examples. Taylor & Francis Group, 2017.

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11

Chakraborty, Dev P. Observer Performance Methods for Diagnostic Imaging: Foundations, Modeling, and Applications with R-Based Examples. Taylor & Francis Group, 2017.

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12

Chakraborty, Dev P. Observer Performance Methods for Diagnostic Imaging. Taylor & Francis Group, 2021.

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13

Chakraborty, Dev P. Observer Performance Methods for Diagnostic Imaging: Foundations, Modeling, and Applications with R-Based Examples. Taylor & Francis Group, 2017.

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14

Schwitter, Juerg. Coronary artery disease. Edited by Dudley Pennell. Oxford University Press, 2018. http://dx.doi.org/10.1093/med/9780198784906.003.0105.

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In the work-up of suspected or known coronary artery disease (CAD), cardiovascular magnetic resonance (CMR) is an established technique and it is recommended by most recent guidelines. Stress dobutamine and stress perfusion CMR yield sensitivities and specificities to detect anatomically defined CAD (>50% coronary stenoses) ranging from 83% to 91% and from 83% to 86%, respectively, with areas under the receiver operating characteristic curve (AUCs) of 0.80–0.93. Multicentre trials report AUCs of 0.75–0.91 to detect CAD and showed superiority over scintigraphic techniques. Increasing evidenc

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15

Candela-Toha, Angel, Teresa Tenorio, Aurora Lietor, and Fernando Liaño. Scoring systems in acute kidney injury patients. Edited by Norbert Lameire. Oxford University Press, 2015. http://dx.doi.org/10.1093/med/9780199592548.003.0236.

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The development of severity of illness scoring systems in the intensive care unit was prompted by the high mortality of patients in this setting. The great changes in the field of intensive care medicine have fostered new and more complex generations of scoring systems. There are several versions of the three major models used, APACHE, SAPS, and MPM. Among them, APACHE II remains the most frequently used. When these generic models are applied to acute kidney injury (AKI) patients, their discrimination ability measured by the area under the receiver operating characteristic curve is about 0.8.

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